Postek, Krzysztof creator Zocca, Alessandro Gromicho, Joaquim A. S. Kantor, Jeffrey C. text Cambridge, United Kingdom Cambridge University Press 2024 monographic eng

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xv, 334p. A hands-on Python-based guide to mathematical optimization for undergraduates and graduates in applied math, industrial engineering and operations research programs, as well as practitioners in related fields. Focuses on practical applications, with over 50 Jupyter notebooks and extensive exercises to test understanding 1. Mathematical optimization 2. Linear optimization 3. Mixed-integer linear optimization 4. Network optimization 5. Convex optimization 6. Conic optimization 7. Accounting for uncertainty: Optimization meets reality 8. Robust optimization 9. Stochastic optimization 10. Two-stage problems Appendix A. Linear algebra primer Appendix B. Solutions of selected exercises List of Tables List of Figures Index. Krzysztof Postek [et. al]. Including indexes. Mathematical optimization Python (Computer program language) Mathematical optimization--Computer programs Optimal stopping (Mathematical statistics) 519.60285 T24 POS Z 9781009493505 260313 20260313191039.0